The hardware is the floor.
Working AI is a stack.
LM TEK builds the engineered hardware foundation for sovereign AI deployments. Getting from foundation to deployed, productive AI takes two more layers - system integration and AI consulting - both delivered by partners. We are the centre of that partner network. Take the two-minute assessment below for a personalised starting point, or browse the page directly.
Two-minute assessment.
Five questions. We return a starting point - what to read first, what hardware tier fits, and what kind of partner you should be talking to. Helper, not a gate. Computed in your browser; nothing leaves the page.
Q 01 / 05
Where are you in the AI journey?
No data leaves this page. Computed in your browser.
Based on what you've told us
Talk to us - we will pre-fill your assessment answers into the routing form so you don't repeat yourself.
Five explainers, one funnel.
The assessment routes you to the right one. If you skipped, here is the cluster - start with foundations if you're newer to the territory, or jump directly to the explainer that matches your situation.
Foundations
Track · 4 primers
Four primers that build the AI deployment vocabulary - what generative AI actually is, what workload patterns most deployments take, what a PoC is for, and a 60-term glossary you can keep open in a second tab.
For visitors: Newer to the territory; want the basics before talking to anyone.
Open the foundations trackDeploying AI in your business
Six phases from discovery through ops. Plain-English map of what an AI deployment actually involves before any hardware is bought.
Want a sequenced plan before you commit budget.
ReadAI infrastructure buying guide
Five stages of investment from on-paper sizing to dedicated AI infrastructure. Realistic spend ranges per stage; design principles that protect early spend.
Sizing the first deployment without locking out future growth.
ReadPrivate AI for sensitive data
Six data classes that force sovereign deployment, six regulatory frameworks where it is the response, and an honest cloud-vs-sovereign comparison.
Working with PII, IP, regulated, or classified material.
ReadData readiness for AI
Five readiness dimensions, five common failure modes, and the engagement shape that turns a messy data layer into a documented foundation. Hardware sizing depends on data state.
Have heard "data isn't ready" and want to scope the work.
ReadA working AI deployment has three layers.
The stack from the ground up. Each layer is delivered by a different kind of partner. Most failure modes in enterprise AI come from confusing the layers - buying hardware to solve a consulting problem, or hiring consultants to solve a hardware problem.
Layer 03
AI process consulting & development
Model selection · fine-tuning · evaluation · ops
→ delivers customer value in everyday practice
Layer 02
System integration
Specification · build · install · maintenance
→ turns a server into a deployed, supported system
Layer 01
Hardware platform
Chassis · cooling · power · components
→ the engineered foundation everything else stands on
Four common situations.
If one of these is close to where you are, jump straight in. Each card has a recommended next read and pre-fills the routing form so you don't have to retype your situation.
Scenario 01
"We have a research lab and want to start running open-weight models on our own infrastructure."
Starter-scale platform footprint, an SI partner who knows research-computing facilities, and an AI consultancy familiar with academic and lab teams.
Scenario 02
"We have an enterprise infrastructure team and want a hardware platform we can spec into our own build."
Your in-house team specs and integrates; we support at the hardware layer.
Scenario 03
"We have an executive mandate to deploy sovereign AI but no technical team."
You need an SI and an AI consultancy more than you need to talk to a hardware vendor first.
Scenario 04
"We have AI workloads running on cloud and want to repatriate to private infrastructure."
A migration-savvy SI, a hardware platform sized to the existing workload, and an AI consultancy who has done this before.
Deploying sovereign AI?
Take the assessment, browse the layer model, or jump straight to the routing form. Whatever shape your situation has, we will route you to the right next step.